Here's a twist on the AI spending narrative: companies aren't racing to adopt artificial intelligence because it's exciting. They're doing it because they're terrified of what happens if they don't.
JPMorgan has coined a term for this phenomenon: FOBO, or Fear of Becoming Obsolete. And according to their analysis, this anxiety is turbocharging the AI capital expenditure cycle in ways that optimism alone never could.
When Tech Spending Becomes Existential
Previous technology cycles were driven by the promise of competitive advantage. This one feels different. Enterprises and governments increasingly view AI as essential infrastructure rather than an optional upgrade. The concern isn't about missing out on the next big thing—it's about survival.
Companies worry that falling behind on productivity gains, automation capabilities, and AI-enhanced decision-making creates a gap that widens fast once competitors deploy these tools at scale. That fear explains why AI investment continues at full throttle despite macro headwinds, tighter credit conditions, and persistent concerns about inflated valuations.
Supply Constraints Keep Spending High
JPMorgan expects AI-related capital expenditure to surpass projections yet again in 2026. The reason? Persistent shortages in computing power, energy infrastructure, and data center capacity. These supply-demand imbalances are forcing buyers to commit earlier and spend more aggressively than they might otherwise.
Governments are joining the spending spree too, treating AI capacity as a matter of national competitiveness rather than leaving it entirely to the private sector.
Balance Sheets Can Handle It
For now, the money's there. Leading AI spenders maintain healthy balance sheets, giving them runway to fund near-term buildouts without immediate financial stress. JPMorgan acknowledges that funding pressure could intensify over the long haul, but the current investment trajectory looks sustainable enough to keep momentum going.
That financial cushion matters because it keeps the capex cycle humming even as skeptics question when returns will materialize.
Show Me The Money
The next phase is all about monetization. JPMorgan anticipates 2026 will deliver more tangible evidence of revenue generation and cost savings, particularly in labor-heavy industries that haven't yet incorporated AI efficiency gains into their forecasts.
The underlying logic is simple: AI spending can't slow down because the cost of falling behind has become too steep. When investment is driven by fear of obsolescence rather than hope for advantage, the calculus changes completely.